Nuclear medicine imaging systems, also known as gamma cameras, are used to determine the distribution of a radio pharmaceutical which is introduced into the body of the patient. Gamma cameras fall into two broad categories, those which determined the occurrence of a radioactive event based on the acquisition of a single photon at a detector and those which determine the presence of such an event based on the coincident acquisition of photons at two detectors on opposite sides of the patient. The first category includes planar gamma cameras and SPECT cameras while the second category includes PET (Positron Emission Tomograph) in which the radioactive events generate two gamma rays which are emitted in opposite directions from the position of the event. The path of these directions is referred to as the line of flight (LOF) (or LOR--line of reaction) and is determined as the line connecting two detected interactions on detectors situated on opposite sides of the patient.
Another way of categorizing gamma cameras is by the type of image which is finally constructed from the acquired data. One category of image is a planar image. The other type is a tomographic (three-dimensional) image.
Gamma cameras of all types require calibration. Calibrations can relate to corrections for the intrinsic lack of accuracy of the detectors themselves. Such corrections include energy correction, linearity correction, rate correction and sensitivity corrections. Exemplary corrections of this type are described, for example in U.S. Pat. Nos. 4,424,446 and 4,588,897, the disclosures of which are incorporated herein by reference. At least some of these corrections are generally necessary for most types of detectors whether they are used for acquiring planar images or for acquiring tomographic images.
When data is acquired for the construction of tomographic images utilizing non-stationary detectors, such as single or dual detectors which rotate about the patient and acquire data for SPECT images, the position of the detectors as they rotate must also be determined so that the information from the various views of the patient may be properly associated in forming the tomographic image. Generating corrections for sagging and other unwanted movement of the detectors as they rotate about the patient is described, for example in U.S. patent application Ser. No. 08/562,375, filed Nov. 24, 1995, now U.S. Pat. No. 5,689,175 the disclosure of which are incorporated herein by reference.
PET images, which are one class of tomographic images, are generally acquired using stationary rings of detectors surrounding the patient. Thus, in general, PET imagers of this type do not need position correction of the type required by SPECT imagers.
The present invention, in some aspects thereof, is concerned with the calibration of gamma camera systems which utilize two or more planar detectors, placed on opposite sides of the patient, to acquire data for the construction of PET images. During acquisition, these detectors are rotated around the patient so that data from a plurality of detector positions can be acquired. Methodology for the construction of PET images is well known in the art. In the past, correction factors for the system operating as a single photon imager and geometrical alignment factors for SPECT were determined. Due to the uncollimated nature of coincident data acquisition, the calibration method applied to parallel hole SPECT do not generally apply to PET. In one exemplary PET calibration process, a virtual collimation process is executed by rebinning the coincidence data into parallel projections. However, this rebinning process is itself dependent on a prior knowledge of the proper calibration parameters. Consequently, in this exemplary PET calibration process, the calibration parameters had to be determined in an indirect manner. In particular, it was determined that a correction for dx1+dx2 was required (where dx1 and dx2 are the transaxial positions on the detector). This correction was derived by acquiring an image of a line source and reconstructing the image. The correction was varied until the image was optimized. This process was repeated several times until a maximal improvement was achieved.